Introduction to Artificial Intelligence for General Surgeons: A Narrative Review

Area of Science:

• Medical Informatics
• Surgical Technology

Background:

• Artificial intelligence (AI) is rapidly advancing and poised for integration into trauma and surgical systems.
• Surgeons frequently face complex, time-sensitive decisions with incomplete information in trauma care.

Purpose of the Study:

• To provide general surgeons with foundational knowledge of AI terminology, processes, and applications.
• To review AI applications specifically within thoraco-abdominal trauma care.
• To discuss the implications of AI integration into the Australian healthcare system.

Main Methods:

• This narrative review synthesizes existing literature on AI in trauma care.
• Focuses on machine learning and deep learning applications.
• Explores subfields like natural language processing and computer vision.

Main Results:

• AI research in trauma predominantly centers on diagnostics, risk prediction, and decision support using machine learning and deep learning.
• Current clinical implementation of AI tools in trauma care remains limited.
• Subfields such as natural language processing and computer vision also show potential.

Conclusions:

• AI holds considerable promise for augmenting all phases of trauma care (pre-operative, intra-operative, post-operative).
• Further prospective, locally validated research is essential before widespread clinical adoption.
• Bridging the knowledge gap among surgeons regarding AI is crucial for effective integration.